Basis for Herbicide Resistance in Canadian Populations of Wild Oat (<i>Avena fatua</i>)
Bibliographic record
Abstract
Wild oat is the second-most abundant, but most economically important, weed across the Canadian Prairies of western Canada. Despite the serious economic effects of resistance to acetyl-CoA carboxylase (ACC) or acetolactate synthase (ALS) inhibitors or both in this weed throughout the Northern Great Plains of North America, little research has examined the basis for herbicide resistance. We investigated target-site and nontarget-site mechanisms conferring ACC- and ALS-inhibitor resistance in 16 wild oat populations from across western Canada (four ACC-inhibitor resistant, four ALS-inhibitor resistant, and eight ACC- and ALS-inhibitor resistant). The ACC1 mutations were found in 8 of the 12 ACC inhibitor-resistant populations. The Ile1781Leu mutation was detected in three populations, the Trp2027Cys and Asp2078Gly mutations were in two populations each, and the Trp1999Cys, Ile2041Asn, Cys2088Arg, and Gly2096Ser substitutions were in one population each. Three populations had two ACC1 mutations. Only 2 of the 12 ALS inhibitor-resistant populations had an ALS target-site mutation—Ser653Thr and Ser653Asn substitutions. This is the first global report of ALS target-site mutations in Avena spp. and four previously undocumented ACC1 mutations in wild oat. Based on these molecular analyses, seedlings of five ACC + ALS inhibitor-resistant populations (one with an ACC1 mutation; four with no ACC or ALS mutations) were treated with malathion, a known cytochrome P450 monooxygenase inhibitor, followed by application of one of four ACC- or ALS-inhibiting herbicides. Malathion treatment often resulted in control or suppression of these populations, suggesting involvement of this enzyme system in contributing to resistance to both ACC and ALS inhibitors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".